akdogan 1.1.0

Universal LLM-optimized project snapshot tool

akdogan — Universal LLM-Optimized Project Snapshot Tool

akdogan is a lightweight, cross-platform tool designed to bridge the gap between complex software projects and Large Language Models (LLMs).

It instantly converts your entire project—directory structure, source code, and data previews—into a single, structured .txt file optimized for the context windows of ChatGPT, Claude, Gemini, and Llama.

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🧠 Why Use akdogan?

Developers often struggle to share code context with AI because:

• ZIP files are often rejected or hard to parse.
• Copy-pasting dozens of files manually is tedious.
• Binary files (images, pyc) create noise and waste tokens.
• Large CSV/Excel files consume context limits without providing structure.

akdogan solves this by intelligently curating your project into a single, token-efficient text file.

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✨ Key Features

• 📂 Visual Directory Tree: Generates a clean map of your project structure.
• 📄 Smart Content Extraction: Reads .py, .js, .html, .rs, .go and more.
• 📊 Data Previews: Automatically extracts only the first 5 rows of .csv and .xlsx files (skips bulk data).
• 🚫 Noise Filtering: Ignores system files like .git, __pycache__, node_modules, venv, and binary executables.
• 🧪 Dual Mode: Run it from the terminal (CLI) or import it in your Python scripts.
• 🖥️ Cross-Platform: 100% compatible with Windows, macOS, and Linux.

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🚀 Installation

Requires Python 3.8+.

pip install akdogan

📦 CLI Usage

Navigate to your project folder and run:

# Snapshot the current directory
akdogan .

Options

Target a specific directory:

akdogan /Users/berke/dev/my-cool-project

Save to a specific output file:

akdogan . -o context_for_gpt.txt

🐍 Python Library Usage

You can also use akdogan programmatically within your automation scripts:

import akdogan

# Generate snapshot for the current directory
akdogan.snapshot('.')

# Or target a specific path
akdogan.snapshot('/path/to/target')

This will generate a file named snapshot_<folder>_<timestamp>.txt automatically.

📁 Output Format Example

The generated text file is structured specifically for LLM comprehension:

=== PROJECT TREE ===

my_project/
    ├── app.py
    ├── utils/
    │   └── helper.py
    └── data/
        └── dataset.csv

=== FILE CONTENTS ===

--- FILE: app.py ---
import os
def main():
    print("Hello World")

--- FILE: utils/helper.py ---
def help_me():
    return True

--- FILE: data/dataset.csv ---
id,name,role
1,Alice,Admin
2,Bob,User
<<FIRST 5 ROWS ONLY>>

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🛠 Development

To contribute or modify the tool locally:

Clone the repository:

git clone https://github.com/yourusername/akdogan.git
cd akdogan

Run locally:

python -m akdogan .

Run tests:

pytest

Build package:

python -m build

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📜 License

This project is licensed under the MIT License. See the LICENSE file for details.

Copyright © 2025 Berke Akdoğan